{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "natural-language-processing-tutorial.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/towardsai/tutorials/blob/master/natural_language_processing/natural_language_processing_tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8CbkQnvBVXPv"
      },
      "source": [
        "#Natural Language Processing (NLP) with Python - Tutorial\n",
        "\n",
        "* Tutorial: https://colab.research.google.com/drive/1vt4u8Hp-iQIRSFc633Outvl7t3R34-iJ?usp=sharing#scrollTo=8CbkQnvBVXPv\n",
        "\n",
        "* Github: https://github.com/towardsai/tutorials/tree/master/natural_language_processing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dzRE-7BVREOJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "90c80ca7-6776-43fe-c6f3-53c01c52c1ff"
      },
      "source": [
        "#To get the text file used :\n",
        "!wget https://raw.githubusercontent.com/towardsai/tutorials/master/natural_language_processing/Natural_Language_Processing_Text.txt\n",
        "\n",
        "#To get the image file used :\n",
        "!wget https://raw.githubusercontent.com/towardsai/tutorials/master/natural_language_processing/circle.png"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2021-01-23 22:16:20--  https://raw.githubusercontent.com/towardsai/tutorials/master/natural_language_processing/Natural_Language_Processing_Text.txt\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 679 [text/plain]\n",
            "Saving to: ‘Natural_Language_Processing_Text.txt’\n",
            "\n",
            "\r          Natural_L   0%[                    ]       0  --.-KB/s               \rNatural_Language_Pr 100%[===================>]     679  --.-KB/s    in 0s      \n",
            "\n",
            "2021-01-23 22:16:20 (24.9 MB/s) - ‘Natural_Language_Processing_Text.txt’ saved [679/679]\n",
            "\n",
            "--2021-01-23 22:16:20--  https://raw.githubusercontent.com/towardsai/tutorials/master/natural_language_processing/circle.png\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 9175 (9.0K) [image/png]\n",
            "Saving to: ‘circle.png’\n",
            "\n",
            "circle.png          100%[===================>]   8.96K  --.-KB/s    in 0s      \n",
            "\n",
            "2021-01-23 22:16:20 (83.2 MB/s) - ‘circle.png’ saved [9175/9175]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "__TNs3DOBiC0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 228
        },
        "outputId": "4f331b5e-616b-48fc-e9de-fd47b2634916"
      },
      "source": [
        "#Open the text file :\n",
        "text_file = open(\"Natural_Language_Processing_Text.txt\")\n",
        "\n",
        "#Read the data :\n",
        "text = text_file.read()\n",
        "\n",
        "#Datatype of the data read :\n",
        "print (type(text))\n",
        "print(\"\\n\")\n",
        "\n",
        "#Print the text :\n",
        "print(text)\n",
        "print(\"\\n\")\n",
        "#Length of the text :\n",
        "print (len(text))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'str'>\n",
            "\n",
            "\n",
            "Once upon a time there was an old mother pig who had three little pigs and not enough food to feed them. So when they were old enough, she sent them out into the world to seek their fortunes.\n",
            "\n",
            "The first little pig was very lazy. He didn't want to work at all and he built his house out of straw. The second little pig worked a little bit harder but he was somewhat lazy too and he built his house out of sticks. Then, they sang and danced and played together the rest of the day.\n",
            "\n",
            "The third little pig worked hard all day and built his house with bricks. It was a sturdy house complete with a fine fireplace and chimney. It looked like it could withstand the strongest winds.\n",
            "\n",
            "\n",
            "675\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kk-wDQ4zdAvF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 832
        },
        "outputId": "9f1aa82d-01d5-41c2-9097-ad6d18b3a924"
      },
      "source": [
        "#Import required libraries :\n",
        "import nltk\n",
        "from nltk import sent_tokenize\n",
        "from nltk import word_tokenize\n",
        "\n",
        "\n",
        "import nltk\n",
        "nltk.download(\"popular\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading collection 'popular'\n",
            "[nltk_data]    | \n",
            "[nltk_data]    | Downloading package cmudict to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/cmudict.zip.\n",
            "[nltk_data]    | Downloading package gazetteers to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/gazetteers.zip.\n",
            "[nltk_data]    | Downloading package genesis to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/genesis.zip.\n",
            "[nltk_data]    | Downloading package gutenberg to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/gutenberg.zip.\n",
            "[nltk_data]    | Downloading package inaugural to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/inaugural.zip.\n",
            "[nltk_data]    | Downloading package movie_reviews to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/movie_reviews.zip.\n",
            "[nltk_data]    | Downloading package names to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/names.zip.\n",
            "[nltk_data]    | Downloading package shakespeare to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/shakespeare.zip.\n",
            "[nltk_data]    | Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/stopwords.zip.\n",
            "[nltk_data]    | Downloading package treebank to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/treebank.zip.\n",
            "[nltk_data]    | Downloading package twitter_samples to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/twitter_samples.zip.\n",
            "[nltk_data]    | Downloading package omw to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/omw.zip.\n",
            "[nltk_data]    | Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/wordnet.zip.\n",
            "[nltk_data]    | Downloading package wordnet_ic to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/wordnet_ic.zip.\n",
            "[nltk_data]    | Downloading package words to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping corpora/words.zip.\n",
            "[nltk_data]    | Downloading package maxent_ne_chunker to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping chunkers/maxent_ne_chunker.zip.\n",
            "[nltk_data]    | Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data]    | Downloading package snowball_data to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    | Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]    |     /root/nltk_data...\n",
            "[nltk_data]    |   Unzipping taggers/averaged_perceptron_tagger.zip.\n",
            "[nltk_data]    | \n",
            "[nltk_data]  Done downloading collection popular\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nR2CzbHWdKrH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 211
        },
        "outputId": "dc7b90a8-d359-46dc-e7c0-b3a52478b308"
      },
      "source": [
        "#Tokenize the text by sentences :\n",
        "sentences = sent_tokenize(text)\n",
        "\n",
        "#How many sentences are there? :\n",
        "print (len(sentences))\n",
        "\n",
        "#Print the sentences :\n",
        "#print(sentences)\n",
        "sentences"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "9\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Once upon a time there was an old mother pig who had three little pigs and not enough food to feed them.',\n",
              " 'So when they were old enough, she sent them out into the world to seek their fortunes.',\n",
              " 'The first little pig was very lazy.',\n",
              " \"He didn't want to work at all and he built his house out of straw.\",\n",
              " 'The second little pig worked a little bit harder but he was somewhat lazy too and he built his house out of sticks.',\n",
              " 'Then, they sang and danced and played together the rest of the day.',\n",
              " 'The third little pig worked hard all day and built his house with bricks.',\n",
              " 'It was a sturdy house complete with a fine fireplace and chimney.',\n",
              " 'It looked like it could withstand the strongest winds.']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pUPacHqcdqc1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 107
        },
        "outputId": "0e4da7b8-9a93-4c8c-ef5c-a8d24baaa5c4"
      },
      "source": [
        "#Tokenize the text with words :\n",
        "words = word_tokenize(text)\n",
        "\n",
        "#How many words are there? :\n",
        "print (len(words))\n",
        "print(\"\\n\")\n",
        "\n",
        "#Print words :\n",
        "print (words)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "144\n",
            "\n",
            "\n",
            "['Once', 'upon', 'a', 'time', 'there', 'was', 'an', 'old', 'mother', 'pig', 'who', 'had', 'three', 'little', 'pigs', 'and', 'not', 'enough', 'food', 'to', 'feed', 'them', '.', 'So', 'when', 'they', 'were', 'old', 'enough', ',', 'she', 'sent', 'them', 'out', 'into', 'the', 'world', 'to', 'seek', 'their', 'fortunes', '.', 'The', 'first', 'little', 'pig', 'was', 'very', 'lazy', '.', 'He', 'did', \"n't\", 'want', 'to', 'work', 'at', 'all', 'and', 'he', 'built', 'his', 'house', 'out', 'of', 'straw', '.', 'The', 'second', 'little', 'pig', 'worked', 'a', 'little', 'bit', 'harder', 'but', 'he', 'was', 'somewhat', 'lazy', 'too', 'and', 'he', 'built', 'his', 'house', 'out', 'of', 'sticks', '.', 'Then', ',', 'they', 'sang', 'and', 'danced', 'and', 'played', 'together', 'the', 'rest', 'of', 'the', 'day', '.', 'The', 'third', 'little', 'pig', 'worked', 'hard', 'all', 'day', 'and', 'built', 'his', 'house', 'with', 'bricks', '.', 'It', 'was', 'a', 'sturdy', 'house', 'complete', 'with', 'a', 'fine', 'fireplace', 'and', 'chimney', '.', 'It', 'looked', 'like', 'it', 'could', 'withstand', 'the', 'strongest', 'winds', '.']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JsBVhkCFdsuU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "outputId": "d342ce56-1df7-41b4-f42b-bc1b35d06734"
      },
      "source": [
        "#Import required libraries :\n",
        "from nltk.probability import FreqDist\n",
        "\n",
        "#Find the frequency :\n",
        "fdist = FreqDist(words)\n",
        "\n",
        "#Print 10 most common words :\n",
        "fdist.most_common(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('.', 9),\n",
              " ('and', 7),\n",
              " ('little', 5),\n",
              " ('a', 4),\n",
              " ('was', 4),\n",
              " ('pig', 4),\n",
              " ('the', 4),\n",
              " ('house', 4),\n",
              " ('to', 3),\n",
              " ('out', 3)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LtNIRQvTduKt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "outputId": "19a6b8ce-8303-4a9b-deec-5b6a89d1c7ff"
      },
      "source": [
        "#Plot the graph for fdist :\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fdist.plot(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tUPyjVHrdveU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 107
        },
        "outputId": "8161a23f-2ae5-4081-b123-afe0f1bcaa6b"
      },
      "source": [
        "#Empty list to store words:\n",
        "words_no_punc = []\n",
        "\n",
        "#Removing punctuation marks :\n",
        "for w in words:\n",
        "    if w.isalpha():\n",
        "        words_no_punc.append(w.lower())\n",
        "\n",
        "#Print the words without punctution marks :\n",
        "print (words_no_punc)\n",
        "\n",
        "print (\"\\n\")\n",
        "\n",
        "#Length :\n",
        "print (len(words_no_punc))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['once', 'upon', 'a', 'time', 'there', 'was', 'an', 'old', 'mother', 'pig', 'who', 'had', 'three', 'little', 'pigs', 'and', 'not', 'enough', 'food', 'to', 'feed', 'them', 'so', 'when', 'they', 'were', 'old', 'enough', 'she', 'sent', 'them', 'out', 'into', 'the', 'world', 'to', 'seek', 'their', 'fortunes', 'the', 'first', 'little', 'pig', 'was', 'very', 'lazy', 'he', 'did', 'want', 'to', 'work', 'at', 'all', 'and', 'he', 'built', 'his', 'house', 'out', 'of', 'straw', 'the', 'second', 'little', 'pig', 'worked', 'a', 'little', 'bit', 'harder', 'but', 'he', 'was', 'somewhat', 'lazy', 'too', 'and', 'he', 'built', 'his', 'house', 'out', 'of', 'sticks', 'then', 'they', 'sang', 'and', 'danced', 'and', 'played', 'together', 'the', 'rest', 'of', 'the', 'day', 'the', 'third', 'little', 'pig', 'worked', 'hard', 'all', 'day', 'and', 'built', 'his', 'house', 'with', 'bricks', 'it', 'was', 'a', 'sturdy', 'house', 'complete', 'with', 'a', 'fine', 'fireplace', 'and', 'chimney', 'it', 'looked', 'like', 'it', 'could', 'withstand', 'the', 'strongest', 'winds']\n",
            "\n",
            "\n",
            "132\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b3SqTkNedxYM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "outputId": "8610eecb-b8c9-4803-c97c-44c46281a172"
      },
      "source": [
        "#Frequency distribution :\n",
        "fdist = FreqDist(words_no_punc)\n",
        "\n",
        "fdist.most_common(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('and', 7),\n",
              " ('the', 7),\n",
              " ('little', 5),\n",
              " ('a', 4),\n",
              " ('was', 4),\n",
              " ('pig', 4),\n",
              " ('he', 4),\n",
              " ('house', 4),\n",
              " ('to', 3),\n",
              " ('out', 3)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kotl9nuTdyge",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "outputId": "2c72c256-1ba8-4c5c-88f3-a89444e680d4"
      },
      "source": [
        "#Plot the most common words on grpah:\n",
        "\n",
        "fdist.plot(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "443sa0zKdzpd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 55
        },
        "outputId": "f99f0993-39bb-47fb-b94d-4cfcec5e2f8e"
      },
      "source": [
        "from nltk.corpus import stopwords\n",
        "\n",
        "#List of stopwords\n",
        "stopwords = stopwords.words(\"english\")\n",
        "print(stopwords)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JaRf2eeYd1Zt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 107
        },
        "outputId": "0f695898-ea89-49c1-cf01-71da56ec76dc"
      },
      "source": [
        "#Empty list to store clean words :\n",
        "clean_words = []\n",
        "\n",
        "for w in words_no_punc:\n",
        "    if w not in stopwords:\n",
        "        clean_words.append(w)\n",
        "        \n",
        "print(clean_words)\n",
        "print(\"\\n\")\n",
        "print(len(clean_words))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['upon', 'time', 'old', 'mother', 'pig', 'three', 'little', 'pigs', 'enough', 'food', 'feed', 'old', 'enough', 'sent', 'world', 'seek', 'fortunes', 'first', 'little', 'pig', 'lazy', 'want', 'work', 'built', 'house', 'straw', 'second', 'little', 'pig', 'worked', 'little', 'bit', 'harder', 'somewhat', 'lazy', 'built', 'house', 'sticks', 'sang', 'danced', 'played', 'together', 'rest', 'day', 'third', 'little', 'pig', 'worked', 'hard', 'day', 'built', 'house', 'bricks', 'sturdy', 'house', 'complete', 'fine', 'fireplace', 'chimney', 'looked', 'like', 'could', 'withstand', 'strongest', 'winds']\n",
            "\n",
            "\n",
            "65\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GX7Z3fmEd2hF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "outputId": "a586c44b-673d-4d15-e833-efa8ae20de03"
      },
      "source": [
        "#Frequency distribution :\n",
        "fdist = FreqDist(clean_words)\n",
        "\n",
        "fdist.most_common(10)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('little', 5),\n",
              " ('pig', 4),\n",
              " ('house', 4),\n",
              " ('built', 3),\n",
              " ('old', 2),\n",
              " ('enough', 2),\n",
              " ('lazy', 2),\n",
              " ('worked', 2),\n",
              " ('day', 2),\n",
              " ('upon', 1)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_9bes0f_d3dv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307
        },
        "outputId": "2f84094e-a49e-41ba-d826-8bbda54810d1"
      },
      "source": [
        "#Plot the most common words on grpah:\n",
        "\n",
        "fdist.plot(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WGptyQEDd44c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 366
        },
        "outputId": "ef2cd46a-5102-4ca3-c4a9-e0bd522734d5"
      },
      "source": [
        "#Library to form wordcloud :\n",
        "from wordcloud import WordCloud\n",
        "\n",
        "#Library to plot the wordcloud :\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "#Generating the wordcloud :\n",
        "wordcloud = WordCloud().generate(text)\n",
        "\n",
        "#Plot the wordcloud :\n",
        "plt.figure(figsize = (12, 12)) \n",
        "plt.imshow(wordcloud) \n",
        "\n",
        "#To remove the axis value :\n",
        "plt.axis(\"off\") \n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z56ilmqod6TU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "b27b24c0-37f9-4f3e-cd91-73a32f2907ae"
      },
      "source": [
        "#Import required libraries :\n",
        "import numpy as np\n",
        "from PIL import Image\n",
        "from wordcloud import WordCloud\n",
        "\n",
        "#Here we are going to use a circle image as mask :\n",
        "char_mask = np.array(Image.open(\"circle.png\"))\n",
        "\n",
        "#Generating wordcloud :\n",
        "wordcloud = WordCloud(background_color=\"black\",mask=char_mask).generate(text)\n",
        "\n",
        "#Plot the wordcloud :\n",
        "plt.figure(figsize = (8,8))\n",
        "plt.imshow(wordcloud)\n",
        "\n",
        "#To remove the axis value :\n",
        "plt.axis(\"off\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0EXIjA7vd8EE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "639a8051-23c4-4ce6-f759-c3677155ed72"
      },
      "source": [
        "#Stemming Example :\n",
        "\n",
        "#Import stemming library :\n",
        "from nltk.stem import PorterStemmer\n",
        "\n",
        "porter = PorterStemmer()\n",
        "\n",
        "#Word-list for stemming :\n",
        "word_list = [\"Study\",\"Studying\",\"Studies\",\"Studied\"]\n",
        "\n",
        "for w in word_list:\n",
        "    print(porter.stem(w))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "studi\n",
            "studi\n",
            "studi\n",
            "studi\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rdMUAzybd9eW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "c98dd398-7e48-441b-c87c-bf52bfa21be9"
      },
      "source": [
        "#Stemming Example :\n",
        "\n",
        "#Import stemming library :\n",
        "from nltk.stem import PorterStemmer\n",
        "\n",
        "porter = PorterStemmer()\n",
        "\n",
        "#Word-list for stemming :\n",
        "word_list = [\"studies\",\"leaves\",\"decreases\",\"plays\"]\n",
        "\n",
        "for w in word_list:\n",
        "    print(porter.stem(w))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "studi\n",
            "leav\n",
            "decreas\n",
            "play\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YUDA2PJ5d_T8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "7f7ac67b-f653-4e8d-e509-88d98b6c7576"
      },
      "source": [
        "#Stemming Example :\n",
        "\n",
        "#Import stemming library :\n",
        "from nltk.stem import SnowballStemmer\n",
        "\n",
        "snowball = SnowballStemmer(\"english\")\n",
        "\n",
        "#Word-list for stemming :\n",
        "word_list = [\"Study\",\"Studying\",\"Studies\",\"Studied\"]\n",
        "\n",
        "for w in word_list:\n",
        "    print(snowball.stem(w))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "studi\n",
            "studi\n",
            "studi\n",
            "studi\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CSPFh_QGeAxQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "outputId": "7fc99057-d0ab-4a10-c3c1-c10f2a6dcc62"
      },
      "source": [
        "#Stemming Example :\n",
        "\n",
        "#Import stemming library :\n",
        "from nltk.stem import SnowballStemmer\n",
        "\n",
        "#Print languages supported :\n",
        "SnowballStemmer.languages"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('arabic',\n",
              " 'danish',\n",
              " 'dutch',\n",
              " 'english',\n",
              " 'finnish',\n",
              " 'french',\n",
              " 'german',\n",
              " 'hungarian',\n",
              " 'italian',\n",
              " 'norwegian',\n",
              " 'porter',\n",
              " 'portuguese',\n",
              " 'romanian',\n",
              " 'russian',\n",
              " 'spanish',\n",
              " 'swedish')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mwnV6hy3eCKs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "2bcb8dc9-d134-44f7-e439-c58c94cc8376"
      },
      "source": [
        "from nltk import WordNetLemmatizer\n",
        "\n",
        "lemma = WordNetLemmatizer()\n",
        "word_list = [\"Study\",\"Studying\",\"Studies\",\"Studied\"]\n",
        "\n",
        "for w in word_list:\n",
        "    print(lemma.lemmatize(w ,pos=\"v\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Study\n",
            "Studying\n",
            "Studies\n",
            "Studied\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NteiC9AleDSb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "8f3c78b3-ddf1-42fb-9bc7-221770ef80bc"
      },
      "source": [
        "from nltk import WordNetLemmatizer\n",
        "\n",
        "lemma = WordNetLemmatizer()\n",
        "word_list = [\"am\",\"is\",\"are\",\"was\",\"were\"]\n",
        "\n",
        "for w in word_list:\n",
        "    print(lemma.lemmatize(w ,pos=\"v\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "be\n",
            "be\n",
            "be\n",
            "be\n",
            "be\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cKpErUbHeEhX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "4d06d54c-244e-4659-8d63-092de9273643"
      },
      "source": [
        "from nltk.stem import PorterStemmer\n",
        " \n",
        "stemmer = PorterStemmer()\n",
        " \n",
        "print(stemmer.stem('studies'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "studi\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-qdgl4JeFpO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "d39638b6-d416-4c4b-b27e-15b9822fdbe7"
      },
      "source": [
        "from nltk.stem import WordNetLemmatizer\n",
        " \n",
        "lemmatizer = WordNetLemmatizer()\n",
        " \n",
        "print(lemmatizer.lemmatize('studies'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "study\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XDBbV6k_eHRl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "5ad4d9af-a6eb-4c31-d60d-533adb9cf1bd"
      },
      "source": [
        "from nltk.stem import WordNetLemmatizer\n",
        " \n",
        "lemmatizer = WordNetLemmatizer()\n",
        " \n",
        "print(lemmatizer.lemmatize('studies'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "study\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AVZ8q1a2eIm8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "6619bb5d-0e5e-436f-d98c-96051fa84efe"
      },
      "source": [
        "from nltk.stem import WordNetLemmatizer\n",
        " \n",
        "lemmatizer = WordNetLemmatizer()\n",
        "print(lemmatizer.lemmatize('studying', pos=\"v\"))\n",
        "print(lemmatizer.lemmatize('studying', pos=\"n\"))\n",
        "print(lemmatizer.lemmatize('studying', pos=\"a\"))\n",
        "print(lemmatizer.lemmatize('studying', pos=\"r\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "study\n",
            "studying\n",
            "studying\n",
            "studying\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TLBjhAnReJwJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "5bc13df8-0b24-43c5-bde8-001cae474eed"
      },
      "source": [
        "from nltk import WordNetLemmatizer\n",
        "\n",
        "lemma = WordNetLemmatizer()\n",
        "word_list = [\"studies\",\"leaves\",\"decreases\",\"plays\"]\n",
        "\n",
        "for w in word_list:\n",
        "    print(lemma.lemmatize(w))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "study\n",
            "leaf\n",
            "decrease\n",
            "play\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4AaooJeeeLQJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "0ea09c55-d300-40a7-b5ec-a53527d4d84a"
      },
      "source": [
        "#PoS tagging :\n",
        "tag = nltk.pos_tag([\"Studying\",\"Study\"])\n",
        "print (tag)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[('Studying', 'VBG'), ('Study', 'NN')]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i3DEiFVPeMu0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "outputId": "0c2e667c-feff-40c3-b22d-5c4f1299f60d"
      },
      "source": [
        "#PoS tagging example :\n",
        "\n",
        "sentence = \"A very beautiful young lady is walking on the beach\"\n",
        "\n",
        "#Tokenizing words :\n",
        "tokenized_words = word_tokenize(sentence)\n",
        "\n",
        "for words in tokenized_words:\n",
        "    tagged_words = nltk.pos_tag(tokenized_words)\n",
        "    \n",
        "tagged_words"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('A', 'DT'),\n",
              " ('very', 'RB'),\n",
              " ('beautiful', 'JJ'),\n",
              " ('young', 'JJ'),\n",
              " ('lady', 'NN'),\n",
              " ('is', 'VBZ'),\n",
              " ('walking', 'VBG'),\n",
              " ('on', 'IN'),\n",
              " ('the', 'DT'),\n",
              " ('beach', 'NN')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ed4f86LjeQU2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "outputId": "572725cc-1e1a-4a8a-b1c5-5929ac14735f"
      },
      "source": [
        "#Extracting Noun Phrase from text :\n",
        "\n",
        "# ? - optional character\n",
        "# * - 0 or more repetations\n",
        "grammar = \"NP : {<DT>?<JJ>*<NN>} \"\n",
        "import matplotlib.pyplot as plt\n",
        "#Creating a parser :\n",
        "parser = nltk.RegexpParser(grammar)\n",
        "\n",
        "#Parsing text :\n",
        "output = parser.parse(tagged_words)\n",
        "print (output)\n",
        "\n",
        "#To visualize :\n",
        "#output.draw()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(S\n",
            "  A/DT\n",
            "  very/RB\n",
            "  (NP beautiful/JJ young/JJ lady/NN)\n",
            "  is/VBZ\n",
            "  walking/VBG\n",
            "  on/IN\n",
            "  (NP the/DT beach/NN))\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_TUHFtD0eRru",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "b0278e24-07d6-40cc-e662-0beb2b888598"
      },
      "source": [
        "#Chinking example :\n",
        "# * - 0 or more repetations\n",
        "# + - 1 or more repetations\n",
        "\n",
        "#Here we are taking the whole string and then\n",
        "#excluding adjectives from that chunk.\n",
        "\n",
        "grammar = r\"\"\" NP: {<.*>+} \n",
        "               }<JJ>+{\"\"\"\n",
        "\n",
        "#Creating parser :\n",
        "parser = nltk.RegexpParser(grammar)\n",
        "\n",
        "#parsing string :\n",
        "output = parser.parse(tagged_words)\n",
        "print(output)\n",
        "\n",
        "#To visualize :\n",
        "#output.draw()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(S\n",
            "  (NP A/DT very/RB)\n",
            "  beautiful/JJ\n",
            "  young/JJ\n",
            "  (NP lady/NN is/VBZ walking/VBG on/IN the/DT beach/NN))\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BYrmBSHieSRe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 260
        },
        "outputId": "13465e36-fcdd-4006-8d93-764c0f82abc5"
      },
      "source": [
        "#Sentence for NER :\n",
        "sentence = \"Mr. Smith made a deal on a beach of Switzerland near WHO.\"\n",
        "\n",
        "#Tokenizing words :\n",
        "tokenized_words = word_tokenize(sentence)\n",
        "\n",
        "#PoS tagging :\n",
        "for w in tokenized_words:\n",
        "    tagged_words = nltk.pos_tag(tokenized_words)\n",
        "\n",
        "#print (tagged_words)\n",
        "\n",
        "#Named Entity Recognition :\n",
        "N_E_R = nltk.ne_chunk(tagged_words,binary=False)\n",
        "print(N_E_R)\n",
        "\n",
        "#To visualize :\n",
        "#N_E_R.draw()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(S\n",
            "  (PERSON Mr./NNP)\n",
            "  (PERSON Smith/NNP)\n",
            "  made/VBD\n",
            "  a/DT\n",
            "  deal/NN\n",
            "  on/IN\n",
            "  a/DT\n",
            "  beach/NN\n",
            "  of/IN\n",
            "  (GPE Switzerland/NNP)\n",
            "  near/IN\n",
            "  (ORGANIZATION WHO/NNP)\n",
            "  ./.)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F5pzo1JKeT48",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 243
        },
        "outputId": "d13c4a96-0c0b-4420-f04f-de54143e205f"
      },
      "source": [
        "#Sentence for NER :\n",
        "sentence = \"Mr. Smith made a deal on a beach of Switzerland near WHO.\"\n",
        "\n",
        "#Tokenizing words :\n",
        "tokenized_words = word_tokenize(sentence)\n",
        "\n",
        "#PoS tagging :\n",
        "for w in tokenized_words:\n",
        "    tagged_words = nltk.pos_tag(tokenized_words)\n",
        "\n",
        "#print (tagged_words)\n",
        "\n",
        "#Named Entity Recognition :\n",
        "N_E_R = nltk.ne_chunk(tagged_words,binary=True)\n",
        "\n",
        "print(N_E_R)\n",
        "\n",
        "#To visualize :\n",
        "#N_E_R.draw()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(S\n",
            "  (NE Mr./NNP Smith/NNP)\n",
            "  made/VBD\n",
            "  a/DT\n",
            "  deal/NN\n",
            "  on/IN\n",
            "  a/DT\n",
            "  beach/NN\n",
            "  of/IN\n",
            "  (NE Switzerland/NNP)\n",
            "  near/IN\n",
            "  (NE WHO/NNP)\n",
            "  ./.)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g1S1GB4SeVed",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "95147bb9-5be0-4080-cefc-1fcff5081c33"
      },
      "source": [
        "#Import wordnet :\n",
        "from nltk.corpus import wordnet\n",
        "\n",
        "for words in wordnet.synsets(\"Fun\"): \n",
        "    print(words)      "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Synset('fun.n.01')\n",
            "Synset('fun.n.02')\n",
            "Synset('fun.n.03')\n",
            "Synset('playfulness.n.02')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Hl5yXEqeXOc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "outputId": "c901794f-18fa-4e85-ca71-7330a67cf964"
      },
      "source": [
        "#Word meaning with definitions :\n",
        "for words in wordnet.synsets(\"Fun\"): \n",
        "    print(words.name())\n",
        "    print(words.definition())\n",
        "    print(words.examples())\n",
        "    \n",
        "    for lemma in words.lemmas(): \n",
        "        print(lemma)\n",
        "    print(\"\\n\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "fun.n.01\n",
            "activities that are enjoyable or amusing\n",
            "['I do it for the fun of it', 'he is fun to have around']\n",
            "Lemma('fun.n.01.fun')\n",
            "Lemma('fun.n.01.merriment')\n",
            "Lemma('fun.n.01.playfulness')\n",
            "\n",
            "\n",
            "fun.n.02\n",
            "verbal wit or mockery (often at another's expense but not to be taken seriously)\n",
            "['he became a figure of fun', 'he said it in sport']\n",
            "Lemma('fun.n.02.fun')\n",
            "Lemma('fun.n.02.play')\n",
            "Lemma('fun.n.02.sport')\n",
            "\n",
            "\n",
            "fun.n.03\n",
            "violent and excited activity\n",
            "['she asked for money and then the fun began', 'they began to fight like fun']\n",
            "Lemma('fun.n.03.fun')\n",
            "\n",
            "\n",
            "playfulness.n.02\n",
            "a disposition to find (or make) causes for amusement\n",
            "['her playfulness surprised me', 'he was fun to be with']\n",
            "Lemma('playfulness.n.02.playfulness')\n",
            "Lemma('playfulness.n.02.fun')\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_iuOvWeteYoN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        },
        "outputId": "3bf77c78-0a3f-4e7c-c80b-541e8a8fb8a7"
      },
      "source": [
        "#How many differnt meanings :\n",
        "for words in wordnet.synsets(\"Fun\"): \n",
        "    for lemma in words.lemmas(): \n",
        "        print(lemma)\n",
        "    print(\"\\n\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Lemma('fun.n.01.fun')\n",
            "Lemma('fun.n.01.merriment')\n",
            "Lemma('fun.n.01.playfulness')\n",
            "\n",
            "\n",
            "Lemma('fun.n.02.fun')\n",
            "Lemma('fun.n.02.play')\n",
            "Lemma('fun.n.02.sport')\n",
            "\n",
            "\n",
            "Lemma('fun.n.03.fun')\n",
            "\n",
            "\n",
            "Lemma('playfulness.n.02.playfulness')\n",
            "Lemma('playfulness.n.02.fun')\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JQUAaYDbeaQM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        },
        "outputId": "9bb8e5f8-153b-4e2d-af73-1f84dd07deff"
      },
      "source": [
        "word = wordnet.synsets(\"Play\")[0]\n",
        "\n",
        "#Checking name :\n",
        "print(word.name())\n",
        "\n",
        "#Checking definition :\n",
        "print(word.definition())\n",
        "\n",
        "#Checking examples:\n",
        "print(word.examples())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "play.n.01\n",
            "a dramatic work intended for performance by actors on a stage\n",
            "['he wrote several plays but only one was produced on Broadway']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kkmDDmInebb6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "e2b0fb9b-571e-4f58-c525-365d111c7e94"
      },
      "source": [
        "word = wordnet.synsets(\"Play\")[0]\n",
        "\n",
        "#Find more abstract term :\n",
        "print(word.hypernyms())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[Synset('dramatic_composition.n.01')]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rpFeTM-Bec8V",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "outputId": "78063b72-a65f-4815-99ea-5243a3eb3135"
      },
      "source": [
        "word = wordnet.synsets(\"Play\")[0]\n",
        "\n",
        "#Find more specific term :\n",
        "word.hyponyms()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Synset('grand_guignol.n.01'),\n",
              " Synset('miracle_play.n.01'),\n",
              " Synset('morality_play.n.01'),\n",
              " Synset('mystery_play.n.01'),\n",
              " Synset('passion_play.n.01'),\n",
              " Synset('playlet.n.01'),\n",
              " Synset('satyr_play.n.01'),\n",
              " Synset('theater_of_the_absurd.n.01')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-co9eRcRefoK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "aa55f4af-8194-4c9a-d9f5-ebe674529b62"
      },
      "source": [
        "word = wordnet.synsets(\"Play\")[0]\n",
        "\n",
        "#Get only name :\n",
        "print(word.lemmas()[0].name())\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "play\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZbzP3baNegP3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "8b5ea6c7-90c8-483c-9257-4f1a0f4cd47d"
      },
      "source": [
        "#Finding synonyms :\n",
        "\n",
        "#Empty list to store synonyms :\n",
        "synonyms = []\n",
        "\n",
        "for words in wordnet.synsets('Fun'):\n",
        "    for lemma in words.lemmas():\n",
        "        synonyms.append(lemma.name())\n",
        "        \n",
        "synonyms"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['fun',\n",
              " 'merriment',\n",
              " 'playfulness',\n",
              " 'fun',\n",
              " 'play',\n",
              " 'sport',\n",
              " 'fun',\n",
              " 'playfulness',\n",
              " 'fun']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qf7KzP2cehvs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "5ce1f3e0-8e83-4c6f-d934-3b8cf0100214"
      },
      "source": [
        "#Finding antonyms :\n",
        "\n",
        "#Empty list to store antonyms :\n",
        "antonyms = []\n",
        "\n",
        "for words in wordnet.synsets('Natural'):\n",
        "    for lemma in words.lemmas():\n",
        "        if lemma.antonyms():\n",
        "            antonyms.append(lemma.antonyms()[0].name())\n",
        "            \n",
        "#Print antonyms :            \n",
        "antonyms"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['unnatural', 'artificial', 'supernatural', 'flat']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ivQlf_e7ejNX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 107
        },
        "outputId": "35829ebf-da8f-49c6-8f9a-85ff30e870fe"
      },
      "source": [
        "#Finding synonyms and antonyms :\n",
        "\n",
        "#Empty lists to store synonyms/antonynms : \n",
        "synonyms = []\n",
        "antonyms = []\n",
        "\n",
        "for words in wordnet.synsets('New'):\n",
        "    for lemma in words.lemmas():\n",
        "        synonyms.append(lemma.name())\n",
        "        if lemma.antonyms():\n",
        "            antonyms.append(lemma.antonyms()[0].name())\n",
        "            \n",
        "#Print lists :\n",
        "print(synonyms)\n",
        "print(\"\\n\")\n",
        "print(antonyms)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['new', 'fresh', 'new', 'novel', 'raw', 'new', 'new', 'unexampled', 'new', 'new', 'newfangled', 'new', 'New', 'Modern', 'New', 'new', 'young', 'new', 'newly', 'freshly', 'fresh', 'new']\n",
            "\n",
            "\n",
            "['old', 'worn']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AdXqU1BCek2W",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "8f663766-5f80-4159-cb81-ae14c47868b3"
      },
      "source": [
        "#Similarity in words :\n",
        "word1 = wordnet.synsets(\"ship\",\"n\")[0]\n",
        "\n",
        "word2 = wordnet.synsets(\"boat\",\"n\")[0] \n",
        "\n",
        "#Check similarity :\n",
        "print(word1.wup_similarity(word2))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.9090909090909091\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kd_lUIn1emHm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "696ee006-0aa6-449e-c141-8289fcd3c11f"
      },
      "source": [
        "#Similarity in words :\n",
        "word1 = wordnet.synsets(\"ship\",\"n\")[0]\n",
        "\n",
        "word2 = wordnet.synsets(\"bike\",\"n\")[0] \n",
        "\n",
        "#Check similarity :\n",
        "print(word1.wup_similarity(word2)) "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.6956521739130435\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mJFlVmGhenvd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        },
        "outputId": "972eaeb6-4e48-405e-914f-666da3df6cad"
      },
      "source": [
        "#Import required libraries :\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "\n",
        "#Text for analysis :\n",
        "sentences = [\"Jim and Pam travelled by the bus:\",\n",
        "             \"The train was late\",\n",
        "             \"The flight was full.Travelling by flight is expensive\"]\n",
        "\n",
        "#Create an object :\n",
        "cv = CountVectorizer()\n",
        "\n",
        "#Generating output for Bag of Words :\n",
        "B_O_W = cv.fit_transform(sentences).toarray()\n",
        "\n",
        "#Total words with their index in model :\n",
        "print(cv.vocabulary_)\n",
        "print(\"\\n\")\n",
        "\n",
        "#Features :\n",
        "print(cv.get_feature_names())\n",
        "print(\"\\n\")\n",
        "\n",
        "#Show the output :\n",
        "print(B_O_W)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'jim': 7, 'and': 0, 'pam': 9, 'travelled': 12, 'by': 2, 'the': 10, 'bus': 1, 'train': 11, 'was': 14, 'late': 8, 'flight': 4, 'full': 5, 'travelling': 13, 'is': 6, 'expensive': 3}\n",
            "\n",
            "\n",
            "['and', 'bus', 'by', 'expensive', 'flight', 'full', 'is', 'jim', 'late', 'pam', 'the', 'train', 'travelled', 'travelling', 'was']\n",
            "\n",
            "\n",
            "[[1 1 1 0 0 0 0 1 0 1 1 0 1 0 0]\n",
            " [0 0 0 0 0 0 0 0 1 0 1 1 0 0 1]\n",
            " [0 0 1 1 2 1 1 0 0 0 1 0 0 1 1]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IanI1jqLetx8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "outputId": "34e61f4f-fec5-42ef-fe52-ee4dc33afc74"
      },
      "source": [
        "#Import required libraries :\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "\n",
        "#Sentences for analysis :\n",
        "sentences = ['This is the first document','This document is the second document']\n",
        "\n",
        "#Create an object :\n",
        "vectorizer = TfidfVectorizer(norm = None)\n",
        "\n",
        "#Generating output for TF_IDF :\n",
        "X = vectorizer.fit_transform(sentences).toarray()\n",
        "\n",
        "#Total words with their index in model :\n",
        "print(vectorizer.vocabulary_)\n",
        "print(\"\\n\")\n",
        "\n",
        "#Features :\n",
        "print(vectorizer.get_feature_names())\n",
        "print(\"\\n\")\n",
        "\n",
        "#Show the output :\n",
        "print(X)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'this': 5, 'is': 2, 'the': 4, 'first': 1, 'document': 0, 'second': 3}\n",
            "\n",
            "\n",
            "['document', 'first', 'is', 'second', 'the', 'this']\n",
            "\n",
            "\n",
            "[[1.         1.40546511 1.         0.         1.         1.        ]\n",
            " [2.         0.         1.         1.40546511 1.         1.        ]]\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}